AI Engineer (Healthcare SaaS)- Medicat

Banyan Software

4d•$90,000 - $120,000•Remote

About The Position

Banyan Software provides the best permanent home for successful enterprise software companies, their employees, and customers. We are on a mission to acquire, build and grow great enterprise software businesses all over the world that have dominant positions in niche vertical markets. In recent years, Banyan was named the #1 fastest-growing private software company in the US on the Inc. 5000 and amongst the top 10 fastest-growing companies by the Deloitte Technology Fast 500. Founded in 2016 with a permanent capital base setup to preserve the legacy of founders, Banyan focuses on a buy and hold for life strategy for growing software companies that serve specialized vertical markets. About Medicat (One of Banyan's Portfolio Companies) Medicat is building modern software infrastructure for healthcare organizations through our platform, MedicatOne. Our mission is to simplify complex healthcare operations through intuitive software, strong data infrastructure, and intelligent automation. As we expand our platform capabilities, we are investing in AI-driven features that improve how healthcare organizations interact with their data, workflows, and operational systems. We are seeking an experienced AI Engineer to help design and implement AI-native capabilities within MedicatOne. This is a high-impact individual contributor role. This is a hands-on engineering role focused on building production-grade AI capabilities inside a growing healthcare SaaS platform. You will work closely with product leadership and engineering to architect and deploy AI-powered systems that interact with structured healthcare data and operational workflows. The role requires strong technical execution as well as fluency in data analytics and healthcare informatics concepts. This is a build-and-ship role where you will play a key part in translating AI opportunities into real product functionality. In this position, you will help to accelerate engineering performance and drive AI-enabled innovation across Medicat in our workflows and in our SaaS product.

Requirements

5+ years building production SaaS systems
Direct experience building and implementing AI/ML or LLM-based features
Strong experience working with structured data and analytics systems
Experience working with healthcare data or healthcare SaaS environments, including familiarity with the regulatory, privacy, and compliance considerations that shape technical decisions (HIPAA, PHI handling, de-identification)
Demonstrated ability to build and deploy systems end-to-end
Working knowledge of modern AI infrastructure and patterns, including:
LLM API integration (OpenAI, Anthropic, or similar) in production environments
Retrieval-Augmented Generation (RAG): designing retrieval pipelines, chunking strategies, and grounding LLM responses in real data
Vector databases: embedding, indexing, and querying unstructured or semi-structured data
Data modeling and SQL
Data pipelines and analytics workflows and working with large structured datasets
API design and backend services
Working with large, structured datasets

Nice To Haves

Experience with healthcare informatics standards or healthcare data environments is strongly preferred.

Responsibilities

Design and implement AI-powered capabilities within the MedicatOne platform
Integrate modern AI models and services into production workflows
Develop systems that interact with structured application data and APIs
Ensure AI features are reliable, performant, and secure
Work with large datasets related to healthcare operations
Design systems that leverage structured data effectively
Build logic that enables intelligent interpretation of operational data
Collaborate with engineering on data pipelines, schemas, and analytics frameworks
Integrate AI capabilities into existing SaaS architecture
Work with backend engineers to ensure scalable system design
Optimize performance of data-intensive AI workflows
Contribute to platform-level architecture decisions
Ship production-ready AI features quickly and iteratively
Collaborate closely with leadership on prioritization and implementation
Help establish best practices for AI development within the organization